Platform Engineering

Founding Platform Engineer: Finch helps companies grow their go-to-market by turning relationship-building into a repeatable system. We're starting with small in-person events like sales dinners. Finch handles the planning, details, and follow-through so our customers can focus on the relationships, not the logistics.
We have built our waitlist of customers while working with our early design partners. We have some initial software we're demoing that can do the job, and now we're building the team that will take this through the exciting next stages as we put it in customers' hands and iterate quickly.

This is a founding engineering seat at a pre-seed funded startup . High everything: ownership, impact, intensity and a high bar. You'll be the first full-time engineer, and be close to customers as we keep shipping and not always behind-the-scenes. We have our initial funding and the backing of AI House (formerly known as the Allen Institute for AI's “AI2 Incubator”).
Together we'll build a culture of trust, growth, psychological safety, excellence, customer-orientation, and inclusivity. Design and build the platform layer that lets non-technical builders and AI agents ship software collaboratively.
Own infrastructure and DevOps for a fast-moving, AI-native engineering environment.
Build and refine the internal tooling, automation, and guardrails that make AI-assisted development reliable rather than risky.
Ship constantly, learn the full lifecycle of Finch's product and customers, and take features from idea to production.
Help define the engineering culture and practices for every engineer who joins after you.

You live in modern AI-native development workflows. Fluent with AI agent orchestration for software building (software factories, and the like).
You have hands-on experience with infrastructure and DevOps. You're going to be owning environments, deployments, and the systems other builders depend on.
You care about building things that are safe and trustworthy enough for AI agents and non-technical teammates to build on top of, not just fast.
You have a track record of shipping real, production software, ideally with some early-stage (Series A or earlier startup) or high-ownership experience.
Location: in either the San Francisco Bay Area or Seattle, or in the process of relocating (sorry, at this stage we can't help with relocation). And definitely will be spending some time in Seattle immediately after starting.

Experience building platforms, internal tooling, or infrastructure that other builders (human or AI) work on top of including software factories, orchestration, or spec-driven (and validated) output.
Experience designing systems specifically to make AI-agent collaboration safer or more reliable (guardrails, evals, observability).
Bonus: GTM, sales-tech, or events/hospitality domain familiarity.

As the first full-time hire with a solo founder, you'll find generous equity compensation in addition to the pre-seed salary (which will increase after a follow-on raise).
Direct partnership with the founder and real influence over both the product and how it gets built.
The chance to build an AI-native software factory from the ground up.
Over time, investing in training towards your career growth.

Our applications involves replicating the work to be done as closely as possible: doing a building exercise while using AI tools and discussing with the existing team.

How Finch Thinks About Technology, Including AI
I've been building software for decades. AI-native is the future we get to live in now. If thinking about changing your title from “programmer” or “engineer” to a more accurate “builder” still itches, that's OK, but that is how we are building our team. Over time, product folks will use the building blocks that you make to move the product forward. Ensure that security, data flow, and infrastructure are happening as they should.
We'll bring on the latest approaches and technologies where we decide, together, that it makes sense.
We recognize that there are impacts to AI use. We are not blind to these and we care deeply. So ensuring that AI is applied in the right way, using local models where we can (they are getting more competent by the month), and making choices through that lens does matter to us.

Currently it's running on vercel, postgres database, with a vite+react frontend. I expect the database selection to keep, though we could add specialized things if needed.
Long-term we have more experience with AWS and prefer that cloud.
Through AI House we have lots of credits with AWS, GCP, Azure etc. (AI House compute + GPU credits are substantially more generous than any other place, and we also have a pattern of getting early access to new tools from the frontier labs.)
Ship, learn, improve. Mistakes are data. Rough drafts and half-formed ideas are welcome. We use data where we have it and intuition where we don't. JP ( was previously co-founder & CTO at Brightflow AI (a UC Berkeley SkyDeck-accelerated startup) where we raised $20M through Series A.